{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "GEN_1_classify_pytorch.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyO6nDxAwZzuhie/Me2PU86n",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "widgets": {
      "application/vnd.jupyter.widget-state+json": {
        "b24652531f0544df8620dd78ecb34f88": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "state": {
            "_view_name": "HBoxView",
            "_dom_classes": [],
            "_model_name": "HBoxModel",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "box_style": "",
            "layout": "IPY_MODEL_2d58621111564cfebb07bfb8930e044d",
            "_model_module": "@jupyter-widgets/controls",
            "children": [
              "IPY_MODEL_968cb46b3446418a9f7f1d3d51828064",
              "IPY_MODEL_e3c5083c487c4fbf835d4fccd7d962ba"
            ]
          }
        },
        "2d58621111564cfebb07bfb8930e044d": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "968cb46b3446418a9f7f1d3d51828064": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "state": {
            "_view_name": "ProgressView",
            "style": "IPY_MODEL_1526665ef9dd4646b0ad686ecb5a6e4a",
            "_dom_classes": [],
            "description": "",
            "_model_name": "FloatProgressModel",
            "bar_style": "info",
            "max": 1,
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": 1,
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "orientation": "horizontal",
            "min": 0,
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_1a456353a1a742c3821f8d8054593787"
          }
        },
        "e3c5083c487c4fbf835d4fccd7d962ba": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_b13c40f3852a4a5cb29af112c449c0a1",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": " 9920512/? [00:20&lt;00:00, 2263466.24it/s]",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_f84d82a595cb45359d5725ae5a6519a2"
          }
        },
        "1526665ef9dd4646b0ad686ecb5a6e4a": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "ProgressStyleModel",
            "description_width": "initial",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "bar_color": null,
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "1a456353a1a742c3821f8d8054593787": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "b13c40f3852a4a5cb29af112c449c0a1": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "f84d82a595cb45359d5725ae5a6519a2": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "02eb4f694cc946e0aaa83eca69b5b982": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "state": {
            "_view_name": "HBoxView",
            "_dom_classes": [],
            "_model_name": "HBoxModel",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "box_style": "",
            "layout": "IPY_MODEL_3701562482894956904506a85d37bc7e",
            "_model_module": "@jupyter-widgets/controls",
            "children": [
              "IPY_MODEL_5dcfa82957fc43b7bc16082c9e7e5c22",
              "IPY_MODEL_3db1a3ba19dc4e3e972eb37571f4786e"
            ]
          }
        },
        "3701562482894956904506a85d37bc7e": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "5dcfa82957fc43b7bc16082c9e7e5c22": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "state": {
            "_view_name": "ProgressView",
            "style": "IPY_MODEL_a15f016a75504da38d386c4a1155d34d",
            "_dom_classes": [],
            "description": "",
            "_model_name": "FloatProgressModel",
            "bar_style": "success",
            "max": 1,
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": 1,
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "orientation": "horizontal",
            "min": 0,
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_03ba3e71b3c248a1bced52cec792268a"
          }
        },
        "3db1a3ba19dc4e3e972eb37571f4786e": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_47f8069171694aa9af5daa01c5a8358d",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": " 32768/? [00:03&lt;00:00, 8680.15it/s]",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_76af26f206724de38e319f94717a5fa9"
          }
        },
        "a15f016a75504da38d386c4a1155d34d": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "ProgressStyleModel",
            "description_width": "initial",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "bar_color": null,
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "03ba3e71b3c248a1bced52cec792268a": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "47f8069171694aa9af5daa01c5a8358d": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "76af26f206724de38e319f94717a5fa9": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "fc72e9f957e54e39a6ee215df65003f3": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "state": {
            "_view_name": "HBoxView",
            "_dom_classes": [],
            "_model_name": "HBoxModel",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "box_style": "",
            "layout": "IPY_MODEL_adf8e174f7494c90aff867144a947f95",
            "_model_module": "@jupyter-widgets/controls",
            "children": [
              "IPY_MODEL_4eb2f239fb5b4e469b1f962934b8b2c4",
              "IPY_MODEL_d66d9aa526a34a1694c023fa52198b34"
            ]
          }
        },
        "adf8e174f7494c90aff867144a947f95": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "4eb2f239fb5b4e469b1f962934b8b2c4": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "state": {
            "_view_name": "ProgressView",
            "style": "IPY_MODEL_530338f15f53440b90004c34484b3553",
            "_dom_classes": [],
            "description": "",
            "_model_name": "FloatProgressModel",
            "bar_style": "success",
            "max": 1,
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": 1,
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "orientation": "horizontal",
            "min": 0,
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_d3d3a73122ed4f1c89a86d5022c3bc4a"
          }
        },
        "d66d9aa526a34a1694c023fa52198b34": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_e6d0600fb7bd4d4286e4598a50a2bb94",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": " 1654784/? [00:02&lt;00:00, 613079.79it/s]",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_44acd7e97fc2419bb8699df51486601d"
          }
        },
        "530338f15f53440b90004c34484b3553": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "ProgressStyleModel",
            "description_width": "initial",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "bar_color": null,
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "d3d3a73122ed4f1c89a86d5022c3bc4a": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "e6d0600fb7bd4d4286e4598a50a2bb94": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "44acd7e97fc2419bb8699df51486601d": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "79e6ae25fb02408ebd90ed764d39a926": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "state": {
            "_view_name": "HBoxView",
            "_dom_classes": [],
            "_model_name": "HBoxModel",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "box_style": "",
            "layout": "IPY_MODEL_6167cfe334ea49a984036fea05724452",
            "_model_module": "@jupyter-widgets/controls",
            "children": [
              "IPY_MODEL_7e2e605a6938422c8fbd78ff949ab694",
              "IPY_MODEL_2f7687c498b647819f074da7a6c74b1f"
            ]
          }
        },
        "6167cfe334ea49a984036fea05724452": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "7e2e605a6938422c8fbd78ff949ab694": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "state": {
            "_view_name": "ProgressView",
            "style": "IPY_MODEL_67a98d2021d3429291fafed36b4051d6",
            "_dom_classes": [],
            "description": "",
            "_model_name": "FloatProgressModel",
            "bar_style": "success",
            "max": 1,
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": 1,
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "orientation": "horizontal",
            "min": 0,
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_9d11f773b9af4587bf59e6b905bd08f2"
          }
        },
        "2f7687c498b647819f074da7a6c74b1f": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_ebc246d075274e9993d6ede068394150",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": " 8192/? [00:00&lt;00:00, 11580.98it/s]",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_07e4f52489dc48a2881aa58461cf606d"
          }
        },
        "67a98d2021d3429291fafed36b4051d6": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "ProgressStyleModel",
            "description_width": "initial",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "bar_color": null,
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "9d11f773b9af4587bf59e6b905bd08f2": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "ebc246d075274e9993d6ede068394150": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "07e4f52489dc48a2881aa58461cf606d": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        }
      }
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/cxbxmxcx/GenReality/blob/master/GEN_1_classify_pytorch.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NEP8pl8zPyiB"
      },
      "source": [
        "import os\n",
        "import torch\n",
        "import torch.nn as nn\n",
        "from torch.autograd import Variable\n",
        "import torchvision \n",
        "import torchvision.datasets as dset\n",
        "import torchvision.transforms as transforms\n",
        "import torch.nn.functional as F\n",
        "import torch.optim as optim\n",
        "import matplotlib.pyplot as plt\n",
        "import numpy as np"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YzbCYm8HQNU0",
        "outputId": "3ee6dbf2-8dc6-43d0-9729-9d6eed6516a8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 652,
          "referenced_widgets": [
            "b24652531f0544df8620dd78ecb34f88",
            "2d58621111564cfebb07bfb8930e044d",
            "968cb46b3446418a9f7f1d3d51828064",
            "e3c5083c487c4fbf835d4fccd7d962ba",
            "1526665ef9dd4646b0ad686ecb5a6e4a",
            "1a456353a1a742c3821f8d8054593787",
            "b13c40f3852a4a5cb29af112c449c0a1",
            "f84d82a595cb45359d5725ae5a6519a2",
            "02eb4f694cc946e0aaa83eca69b5b982",
            "3701562482894956904506a85d37bc7e",
            "5dcfa82957fc43b7bc16082c9e7e5c22",
            "3db1a3ba19dc4e3e972eb37571f4786e",
            "a15f016a75504da38d386c4a1155d34d",
            "03ba3e71b3c248a1bced52cec792268a",
            "47f8069171694aa9af5daa01c5a8358d",
            "76af26f206724de38e319f94717a5fa9",
            "fc72e9f957e54e39a6ee215df65003f3",
            "adf8e174f7494c90aff867144a947f95",
            "4eb2f239fb5b4e469b1f962934b8b2c4",
            "d66d9aa526a34a1694c023fa52198b34",
            "530338f15f53440b90004c34484b3553",
            "d3d3a73122ed4f1c89a86d5022c3bc4a",
            "e6d0600fb7bd4d4286e4598a50a2bb94",
            "44acd7e97fc2419bb8699df51486601d",
            "79e6ae25fb02408ebd90ed764d39a926",
            "6167cfe334ea49a984036fea05724452",
            "7e2e605a6938422c8fbd78ff949ab694",
            "2f7687c498b647819f074da7a6c74b1f",
            "67a98d2021d3429291fafed36b4051d6",
            "9d11f773b9af4587bf59e6b905bd08f2",
            "ebc246d075274e9993d6ede068394150",
            "07e4f52489dc48a2881aa58461cf606d"
          ]
        }
      },
      "source": [
        "trans = transforms.Compose([transforms.ToTensor(), \n",
        "                            transforms.Normalize((0.5,), (1.0,))])\n",
        "# if not exist, download mnist dataset\n",
        "train_set = dset.MNIST(root='./data',train=True, \n",
        "                       transform=trans, download=True)\n",
        "test_set = dset.MNIST(root='./data',train=False, \n",
        "                      transform=trans, download=True)\n",
        "\n",
        "print(train_set)\n",
        "print(test_set)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Downloading http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz to ./data/MNIST/raw/train-images-idx3-ubyte.gz\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "b24652531f0544df8620dd78ecb34f88",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(FloatProgress(value=1.0, bar_style='info', max=1.0), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Extracting ./data/MNIST/raw/train-images-idx3-ubyte.gz to ./data/MNIST/raw\n",
            "Downloading http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz to ./data/MNIST/raw/train-labels-idx1-ubyte.gz\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "02eb4f694cc946e0aaa83eca69b5b982",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(FloatProgress(value=1.0, bar_style='info', max=1.0), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Extracting ./data/MNIST/raw/train-labels-idx1-ubyte.gz to ./data/MNIST/raw\n",
            "Downloading http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz to ./data/MNIST/raw/t10k-images-idx3-ubyte.gz\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "fc72e9f957e54e39a6ee215df65003f3",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(FloatProgress(value=1.0, bar_style='info', max=1.0), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Extracting ./data/MNIST/raw/t10k-images-idx3-ubyte.gz to ./data/MNIST/raw\n",
            "Downloading http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz to ./data/MNIST/raw/t10k-labels-idx1-ubyte.gz\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "79e6ae25fb02408ebd90ed764d39a926",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(FloatProgress(value=1.0, bar_style='info', max=1.0), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Extracting ./data/MNIST/raw/t10k-labels-idx1-ubyte.gz to ./data/MNIST/raw\n",
            "Processing...\n",
            "Done!\n",
            "Dataset MNIST\n",
            "    Number of datapoints: 60000\n",
            "    Root location: ./data\n",
            "    Split: Train\n",
            "    StandardTransform\n",
            "Transform: Compose(\n",
            "               ToTensor()\n",
            "               Normalize(mean=(0.5,), std=(1.0,))\n",
            "           )\n",
            "Dataset MNIST\n",
            "    Number of datapoints: 10000\n",
            "    Root location: ./data\n",
            "    Split: Test\n",
            "    StandardTransform\n",
            "Transform: Compose(\n",
            "               ToTensor()\n",
            "               Normalize(mean=(0.5,), std=(1.0,))\n",
            "           )\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/pytorch/torch/csrc/utils/tensor_numpy.cpp:141: UserWarning: The given NumPy array is not writeable, and PyTorch does not support non-writeable tensors. This means you can write to the underlying (supposedly non-writeable) NumPy array using the tensor. You may want to copy the array to protect its data or make it writeable before converting it to a tensor. This type of warning will be suppressed for the rest of this program.\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SWB0sjGPQ9pL",
        "outputId": "8d4fdf74-fc59-47ee-cb68-ba40d332296a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 50
        }
      },
      "source": [
        "batch_size = 64\n",
        "\n",
        "train_loader = torch.utils.data.DataLoader(\n",
        "                 dataset=train_set,\n",
        "                 batch_size=batch_size,\n",
        "                 shuffle=True)\n",
        "test_loader = torch.utils.data.DataLoader(\n",
        "                dataset=test_set,\n",
        "                batch_size=batch_size,\n",
        "                shuffle=False)\n",
        "\n",
        "print(len(train_loader))\n",
        "print(len(test_loader))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "938\n",
            "157\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mU9Y0M2knja2",
        "outputId": "f5a17394-32a7-4818-993a-afbc268ad221",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 645
        }
      },
      "source": [
        "def imshow(img):\n",
        "  img = img / 2 + 0.5     \n",
        "  npimg = img.numpy()\n",
        "  plt.figure(figsize=(10, 10))\n",
        "  plt.imshow(np.transpose(npimg, (1, 2, 0)))\n",
        "  plt.show()\n",
        "\n",
        "dataiter = iter(train_loader)\n",
        "images, labels = dataiter.next()\n",
        "imshow(torchvision.utils.make_grid(images, nrow=8))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\n",
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 720x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FTw-X4QpRU6t"
      },
      "source": [
        "class MLP(nn.Module):\n",
        "  def __init__(self):\n",
        "    super(MLP, self).__init__()\n",
        "    self.fc1 = nn.Linear(28*28, 500)\n",
        "    self.fc2 = nn.Linear(500, 256)\n",
        "    self.fc3 = nn.Linear(256, 10)\n",
        "  def forward(self, x):\n",
        "    x = x.view(-1, 28*28)\n",
        "    x = torch.relu(self.fc1(x))\n",
        "    x = torch.relu(self.fc2(x))\n",
        "    x = self.fc3(x)\n",
        "    return x\n",
        "  \n",
        "  def name(self):\n",
        "      return \"MLP\""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_xSn_LBQRhNj"
      },
      "source": [
        "model = MLP()\n",
        "optimizer = optim.SGD(model.parameters(), lr=0.01, momentum=0.9)\n",
        "loss_fn = nn.CrossEntropyLoss()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jWxfkhedRu3W",
        "outputId": "1bd082f7-fd94-44a5-c489-15503fea1203",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "epochs = 10\n",
        "history=[]\n",
        "for epoch in range(epochs):  \n",
        "  avg_loss = 0\n",
        "  for batch_idx, (x, y) in enumerate(train_loader):\n",
        "    optimizer.zero_grad()    \n",
        "    x, y = Variable(x), Variable(y)\n",
        "    y_pred = model(x)\n",
        "    loss = loss_fn(y_pred, y)\n",
        "    avg_loss = avg_loss * 0.9 + loss.data * 0.1\n",
        "    history.append(avg_loss)\n",
        "    loss.backward()\n",
        "    optimizer.step()    \n",
        "    if (batch_idx+1) % 100 == 0 or (batch_idx+1) == len(train_loader):\n",
        "      print(f'epoch: {epoch}, batch index:' + \n",
        "            f'{batch_idx+1}, train loss: {avg_loss:.6f}')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "epoch: 0, batch index:100, train loss: 0.899156\n",
            "epoch: 0, batch index:200, train loss: 0.485744\n",
            "epoch: 0, batch index:300, train loss: 0.435377\n",
            "epoch: 0, batch index:400, train loss: 0.353134\n",
            "epoch: 0, batch index:500, train loss: 0.297872\n",
            "epoch: 0, batch index:600, train loss: 0.332928\n",
            "epoch: 0, batch index:700, train loss: 0.291253\n",
            "epoch: 0, batch index:800, train loss: 0.262212\n",
            "epoch: 0, batch index:900, train loss: 0.293839\n",
            "epoch: 0, batch index:938, train loss: 0.275004\n",
            "epoch: 1, batch index:100, train loss: 0.254382\n",
            "epoch: 1, batch index:200, train loss: 0.219830\n",
            "epoch: 1, batch index:300, train loss: 0.204702\n",
            "epoch: 1, batch index:400, train loss: 0.219349\n",
            "epoch: 1, batch index:500, train loss: 0.194614\n",
            "epoch: 1, batch index:600, train loss: 0.173999\n",
            "epoch: 1, batch index:700, train loss: 0.171462\n",
            "epoch: 1, batch index:800, train loss: 0.158827\n",
            "epoch: 1, batch index:900, train loss: 0.145912\n",
            "epoch: 1, batch index:938, train loss: 0.154020\n",
            "epoch: 2, batch index:100, train loss: 0.145611\n",
            "epoch: 2, batch index:200, train loss: 0.159256\n",
            "epoch: 2, batch index:300, train loss: 0.147341\n",
            "epoch: 2, batch index:400, train loss: 0.136164\n",
            "epoch: 2, batch index:500, train loss: 0.127864\n",
            "epoch: 2, batch index:600, train loss: 0.138618\n",
            "epoch: 2, batch index:700, train loss: 0.125314\n",
            "epoch: 2, batch index:800, train loss: 0.126355\n",
            "epoch: 2, batch index:900, train loss: 0.127645\n",
            "epoch: 2, batch index:938, train loss: 0.151965\n",
            "epoch: 3, batch index:100, train loss: 0.112350\n",
            "epoch: 3, batch index:200, train loss: 0.099677\n",
            "epoch: 3, batch index:300, train loss: 0.128958\n",
            "epoch: 3, batch index:400, train loss: 0.106594\n",
            "epoch: 3, batch index:500, train loss: 0.106319\n",
            "epoch: 3, batch index:600, train loss: 0.095895\n",
            "epoch: 3, batch index:700, train loss: 0.101075\n",
            "epoch: 3, batch index:800, train loss: 0.090019\n",
            "epoch: 3, batch index:900, train loss: 0.097741\n",
            "epoch: 3, batch index:938, train loss: 0.131227\n",
            "epoch: 4, batch index:100, train loss: 0.082582\n",
            "epoch: 4, batch index:200, train loss: 0.100162\n",
            "epoch: 4, batch index:300, train loss: 0.066638\n",
            "epoch: 4, batch index:400, train loss: 0.085184\n",
            "epoch: 4, batch index:500, train loss: 0.102155\n",
            "epoch: 4, batch index:600, train loss: 0.097210\n",
            "epoch: 4, batch index:700, train loss: 0.074143\n",
            "epoch: 4, batch index:800, train loss: 0.076063\n",
            "epoch: 4, batch index:900, train loss: 0.081016\n",
            "epoch: 4, batch index:938, train loss: 0.078665\n",
            "epoch: 5, batch index:100, train loss: 0.072608\n",
            "epoch: 5, batch index:200, train loss: 0.085822\n",
            "epoch: 5, batch index:300, train loss: 0.098841\n",
            "epoch: 5, batch index:400, train loss: 0.074796\n",
            "epoch: 5, batch index:500, train loss: 0.061704\n",
            "epoch: 5, batch index:600, train loss: 0.074417\n",
            "epoch: 5, batch index:700, train loss: 0.070602\n",
            "epoch: 5, batch index:800, train loss: 0.072470\n",
            "epoch: 5, batch index:900, train loss: 0.064970\n",
            "epoch: 5, batch index:938, train loss: 0.049571\n",
            "epoch: 6, batch index:100, train loss: 0.058633\n",
            "epoch: 6, batch index:200, train loss: 0.061541\n",
            "epoch: 6, batch index:300, train loss: 0.060313\n",
            "epoch: 6, batch index:400, train loss: 0.063993\n",
            "epoch: 6, batch index:500, train loss: 0.061373\n",
            "epoch: 6, batch index:600, train loss: 0.042550\n",
            "epoch: 6, batch index:700, train loss: 0.037888\n",
            "epoch: 6, batch index:800, train loss: 0.053330\n",
            "epoch: 6, batch index:900, train loss: 0.061909\n",
            "epoch: 6, batch index:938, train loss: 0.068207\n",
            "epoch: 7, batch index:100, train loss: 0.052120\n",
            "epoch: 7, batch index:200, train loss: 0.041034\n",
            "epoch: 7, batch index:300, train loss: 0.042279\n",
            "epoch: 7, batch index:400, train loss: 0.040645\n",
            "epoch: 7, batch index:500, train loss: 0.043481\n",
            "epoch: 7, batch index:600, train loss: 0.042972\n",
            "epoch: 7, batch index:700, train loss: 0.054409\n",
            "epoch: 7, batch index:800, train loss: 0.044723\n",
            "epoch: 7, batch index:900, train loss: 0.051311\n",
            "epoch: 7, batch index:938, train loss: 0.059340\n",
            "epoch: 8, batch index:100, train loss: 0.040238\n",
            "epoch: 8, batch index:200, train loss: 0.031225\n",
            "epoch: 8, batch index:300, train loss: 0.055834\n",
            "epoch: 8, batch index:400, train loss: 0.030887\n",
            "epoch: 8, batch index:500, train loss: 0.059796\n",
            "epoch: 8, batch index:600, train loss: 0.033754\n",
            "epoch: 8, batch index:700, train loss: 0.039597\n",
            "epoch: 8, batch index:800, train loss: 0.041682\n",
            "epoch: 8, batch index:900, train loss: 0.047841\n",
            "epoch: 8, batch index:938, train loss: 0.049212\n",
            "epoch: 9, batch index:100, train loss: 0.025766\n",
            "epoch: 9, batch index:200, train loss: 0.035862\n",
            "epoch: 9, batch index:300, train loss: 0.032535\n",
            "epoch: 9, batch index:400, train loss: 0.057712\n",
            "epoch: 9, batch index:500, train loss: 0.030682\n",
            "epoch: 9, batch index:600, train loss: 0.037085\n",
            "epoch: 9, batch index:700, train loss: 0.062495\n",
            "epoch: 9, batch index:800, train loss: 0.038409\n",
            "epoch: 9, batch index:900, train loss: 0.037130\n",
            "epoch: 9, batch index:938, train loss: 0.032710\n"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}